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A close approximation to maximizing the minimum SNR for ZF receiver is also provided under the assumption of M
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Accuracy of the approximation: To maximize the regularity of the functions generated by the scaling function φ, we require the vanishing of the first J moments of the wavelet in terms of the polynomial Eq. (2.2) Fhboxleft -1right)=Fhboxleft -1right.....={F left -1right1right)=0 (2.5).
In particular, we optimize the hydraulic fracturing design by implementing a variant of the Simultaneous Perturbation Stochastic Approximation algorithm to maximize the net present value of the shale asset, including the cost of fracturing and the revenue from gas production.
In this section, we introduce an approximation algorithm called SPCPM to maximize the energy preservation of a sector-shaped wireless sensor network.
In the above equation, we try to maximize the approximation performance of y i (i = {1,2,…,N|x i (j) ≠ 0}) by x i (j d j, i.e., by the target atom d j and its corresponding representation coefficient x i (j).
Applying the asymptotic formula, we provide an approximation of the optimal investment strategy to maximize the expected terminal wealth subject to a risk constraint on the Value-at-Risk, which is defined with respect to finite-time discounted net loss.
Now, we intend to maximize the sum-rate approximation ∑ k R k with respect to w under the total transmit power constraint.
More specifically, the authors propose an approximation technique for selecting an optimal path set to maximize the probability of successful transmission in cases where paths may not be independent and their failure probability can vary as well.
All chains used the Brownian motion approximation as the mutation model and relied on adaptive heating to maximize the visited space (default parameters).
Using these SINR approximations, a low-complexity power control algorithm is further proposed to maximize the sum SE.
Seeing MTO as the task to maximize the number of satisfied pairs, Medvedovsky et al. also provided polynomial-time approximation algorithms with approximation factor 1 /4 in the case of stars and O(1 /log n) in the case of general n-vertex trees.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com